Rough volatility: Evidence from option prices
By Giulia Livieri, Saad Mouti, Andrea Pallavicini, Mathieu Rosenbaum. IISE Transactions, 2017
102 citations recorded by the source corpus.
ABSTRACT It has been recently shown that spot volatilities can be closely modeled by rough stochastic volatility-type dynamics. In such models, the log-volatility follows a fractional Brownian motion with Hurst parameter smaller than half. This result has been established using high-frequency volatility estimations from historical price data. We revisit this finding by studying implied volatility-based approximations of the spot volatility. Using at-the-money options on the S&P500 index with short maturity, we are able to confirm that volatility is rough. The Hurst parameter found here, of order 0.3, is slightly larger than that usually obtained from historical data. This is easily explained from a smoothing effect due to the remaining time to maturity of the considered options.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/a929d43166f2eef7aa9a0ba3bc2b760d158e8e48
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Paul Jusselin
- Tetsuya Takaishi
- Mathieu Rosenbaum
- Jim Gatheral
- Omar El Euch
- Eduardo Abi Jaber
- Christian-Yann Robert
In Finance
- Paul Jusselin
- Tetsuya Takaishi
- Mathieu Rosenbaum
- Omar El Euch
- Eduardo Abi Jaber
- Jim Gatheral
- Christa Cuchiero
- Xinbing Kong
Citations in the corpus
- Rough volatility of Bitcoin (2019, background): “Within limited statistics, it is difficult to confirm Gaussian for our data set.”
- No‐arbitrage implies power‐law market impact and rough volatility (2018, background): “This stylized fact first established in [15] and confirmed in [4, 24] means that the (log-)volatility process of an asset essentially behaves as a fractional Brownian motion (fBm for short) with Hurst parameter of order 0.”